bootstrap_model         Model bootstrapping
bootstrap_parameters    Parameters bootstrapping
ci.default              Confidence Intervals (CI)
ci_betwithin            Between-within approximation for SEs, CIs and
                        p-values
ci_kenward              Kenward-Roger approximation for SEs, CIs and
                        p-values
ci_ml1                  "m-l-1" approximation for SEs, CIs and p-values
ci_satterthwaite        Satterthwaite approximation for SEs, CIs and
                        p-values
cluster_analysis        Cluster Analysis
cluster_centers         Find the cluster centers in your data
cluster_discrimination
                        Compute a linear discriminant analysis on
                        classified cluster groups
cluster_meta            Metaclustering
cluster_performance     Performance of clustering models
compare_parameters      Compare model parameters of multiple models
convert_efa_to_cfa      Conversion between EFA results and CFA
                        structure
degrees_of_freedom      Degrees of Freedom (DoF)
display.parameters_model
                        Print tables in different output formats
dominance_analysis      Dominance Analysis
equivalence_test.lm     Equivalence test
factor_analysis         Principal Component Analysis (PCA) and Factor
                        Analysis (FA)
factor_scores           Extract factor scores from Factor Analysis
                        (EFA) or Omega
fish                    Sample data set
format.compare_parameters
                        Print comparisons of model parameters
format.parameters_model
                        Print model parameters
format_df_adjust        Format the name of the degrees-of-freedom
                        adjustment methods
format_order            Order (first, second, ...) formatting
format_p_adjust         Format the name of the p-value adjustment
                        methods
format_parameters       Parameter names formatting
get_scores              Get Scores from Principal Component or Factor
                        Analysis (PCA/FA)
model_parameters        Model Parameters
model_parameters.BFBayesFactor
                        Parameters from BayesFactor objects
model_parameters.aov    Parameters from ANOVAs
model_parameters.befa   Parameters from Bayesian Exploratory Factor
                        Analysis
model_parameters.cgam   Parameters from Generalized Additive (Mixed)
                        Models
model_parameters.compare.loo
                        Bayesian Model Comparison
model_parameters.data.frame
                        Parameters from Bayesian Models
model_parameters.default
                        Parameters from (General) Linear Models
model_parameters.glht   Parameters from Hypothesis Testing
model_parameters.glimML
                        Parameters from special models
model_parameters.glmmTMB
                        Parameters from Mixed Models
model_parameters.hclust
                        Parameters from Cluster Models (k-means, ...)
model_parameters.htest
                        Parameters from hypothesis tests
model_parameters.lavaan
                        Parameters from PCA, FA, CFA, SEM
model_parameters.mira   Parameters from multiply imputed repeated
                        analyses
model_parameters.mlm    Parameters from multinomial or cumulative link
                        models
model_parameters.rma    Parameters from Meta-Analysis
model_parameters.t1way
                        Parameters from robust statistical objects in
                        'WRS2'
model_parameters.zcpglm
                        Parameters from Zero-Inflated Models
n_clusters              Find number of clusters in your data
n_factors               Number of components/factors to retain in
                        PCA/FA
p_calibrate             Calculate calibrated p-values.
p_direction.lm          Probability of Direction (pd)
p_function              p-value or consonance function
p_significance.lm       Practical Significance (ps)
p_value                 p-values
parameters-options      Global options from the parameters package
parameters_type         Type of model parameters
pool_parameters         Pool Model Parameters
predict.parameters_clusters
                        Predict method for parameters_clusters objects
qol_cancer              Sample data set
random_parameters       Summary information from random effects
reduce_parameters       Dimensionality reduction (DR) / Features
                        Reduction
reshape_loadings        Reshape loadings between wide/long formats
select_parameters       Automated selection of model parameters
simulate_model          Simulated draws from model coefficients
simulate_parameters     Simulate Model Parameters
sort_parameters         Sort parameters by coefficient values
standard_error          Standard Errors
standardize_info        Get Standardization Information
standardize_parameters
                        Parameters standardization
